AI augments review, it does not replace it

The healthy mental model is simple: AI is a fast first reviewer, never the approver. It clears the mechanical layer so the human reviewer spends attention where judgment is needed. The moment it becomes the reason a change merges, you have traded speed for risk you cannot see.

A real failure comes with this. Because AI review is cheap, teams run it on everything, and the volume becomes its own problem. When most comments are style nitpicks or false alarms, reviewers learn to skip past every comment the tool leaves, including the rare one that mattered. In 2026 the widely cited guidance is that once reviewers ignore a large share of flags, the tool has a false-positive problem, not a coverage win.

So the augment model has two rules. First, AI proposes and a person who understands the blast radius approves — the person who can reason about what breaks if this is wrong. Second, tune for signal over volume: a smaller number of high-confidence comments beats a wall of noise.

A prompt that respects this:

Only raise issues you are confident are real problems in this diff. Skip style preferences. If you are unsure, say so rather than asserting.

Safety angle: never merge code you do not understand. If the only reason a change looks fine is that the AI said so, the review has not happened yet.